PERFORMANCE STUDIES OF TRICKLE BED REACTORS Mohan R
PERFORMANCE STUDIES OF TRICKLE BED REACTORS Mohan R. Khadilkar Thesis Advisors: M. P. Dudukovic and M. H. Al-Dahhan Chemical Reaction Engineering Laboratory Department of Chemical Engineering Washington University St. Louis, Missouri CREL
Objectives and Accomplishments n Examined the current state of the art in experimentation and modeling of trickle beds critically and successfully answered the often asked questions 1. Do upflow and downflow differ? When and Why ? 2. How to get reproducible scale-up data from small scale reactors independent of flow mode? 3. To what extent can current models predict the observed behavior? n Formulated the rigorous approach to trickle bed modeling on pellet and reactor scale and illustrated the effectiveness of this approach for prediction of steady and unsteady state performance n Examined experimentally and via models, unsteady state operation in trickle beds and identified regions of, and, reasons for performance enhancement CREL
Performance of Trickle Bed Reactors 1. Comparison of Trickle Bed and Upflow Effect of Bed Dilution Model Evaluation 2. Rigorous Steady State Model 3. Unsteady State Performance Experiments 4. Rigorous Unsteady State Model Chemical Kinetics Fluid Dynamics Phase Interaction & Contacting Transport Coefficients 5. Transient Fluid Dynamic Simulation Reactor Design & Scale-up Performance CREL
Trickle Bed Reactors Cocurrent Downflow of Gas and Liquid on a Fixed Catalyst Bed Operating Pressures up to 20 MPa Operating Flow Ranges: High Liquid Mass Velocity (Fully Wetted Catalyst) (Suitable for Liquid Limited Reactions) Low Liquid Mass Velocity (Partially Wetted Catalyst) (Suitable for Gas Limited Reactions) Catalyst Wetting Conditions in Trickle Bed Reactor Limiting Reactant criterion: Gas limited reaction if Liquid limited reaction if Flow Map (Fukushima et al. , 1977) CREL
FLOW REGIMES AND CATALYST WETTING EFFECTS DOWNFLOW (TRICKLE BED REACTOR) UPFLOW (PACKED BUBBLE COLUMN) CREL
Motivation n To understand the differences between downflow and upflow operation. Are upflow reactors indicative of trickle bed performance under different reaction conditions? To understand the effects of bed dilution with fines on reactor performance To develop guidelines for scale-up/scale-down of reactors for gas or liquid reactant limited reactions Objectives n n n Experimentally investigate the performance of downflow (Trickle Bed) and upflow (Packed Bubble Column) reactors for a test hydrogenation reaction Study the effects of pressure, feed concentration, gas velocity and bed dilution on the performance of both modes of operation Evaluate available reactor models in comparison with experimental data
Reaction Scheme: Catalyst : 2. 5 % Pd on Alumina (cylindrical 0. 13 cm dia. ) Fines : Silicon carbide 0. 02 cm Alpha-methylstyrene B (l) + A(g) cumene P(l) Range of Experimentation : • Superficial Liquid Velocity (Mass Velocity) : 0. 09 - 0. 5 cm/s (0. 63 -3. 85 kg/m 2 s) • Superficial Gas Velocity (Mass Velocity) : 3. 8 -14. 4 cm/s (3. 3 x 10 -3 -12. 8 x 10 -3 kg/m 2 s) • Feed Concentration • Operating Pressure • Feed Temperature : 3. 1 - 7. 8 % (230 -600 mol/m 3) : 30 - 200 psig (3 -15 atm) : 24 o. C Limiting Reactant criterion: Gas limited reaction if Liquid limited reaction if CREL
Experimental Setup CREL
Downflow and Upflow Experimental Results under Gas and Liquid Limited Conditions without Fines Downflow outperforms upflow due to partial external wetting and improved gas reactant access to particles Upflow outperforms downflow due to more complete external wetting and better transport of liquid reactant to the catalyst CREL
Downflow and Upflow Experimental Results under Gas and Liquid Limited Conditions with Fines ABOUT EQUAL PERFORMANCE DUE TO COMPLETE WETTING Fines Packing Procedure: Vol. of Fines ~Void volume (Al-Dahhan et al. 1995) CREL
Effect of Pressure and Gas Velocity on Performance Transition to Liquid Limited Conditions Negligible Effect of Gas Velocity CREL
Slurry Kinetics CREL
El- Hisnawi (1982) model • Reactor scale plug flow equations Liquid phase gas reactant concentration • Constant effectiveness factor Modified by external contacting efficiency • Allowance for rate enhancement on externally dry catalyst Direct access of gas on inactively wetted pellets. CREL
Beaudry (1987) model • Pellet scale reaction diffusion equations For fully wetted and partially wetted slabs • Effectiveness factor weighted based on contacting efficiency • Overall effectiveness factor changes along the bed length Evaluation of overall effectiveness with change in concentration and contacting Overall Effectiveness factor at any location CREL
Upflow and Downflow Performance at Low Pressure (Gas Limited Condition) Experimental Data and Model Predictions CREL
Upflow and Downflow Performance at High Pressure (Liquid Limited Conditions): Experimental Data and Model Predictions CREL
Summary n DOWNFLOW OUTPERFORMS UPFLOW AT LOW PRESSURE. (Hydrogenation of alpha-methylstyrene is a gas limited reaction. Partial wetting is helpful in this situation. ) n UPFLOW OUTPERFORMS DOWNFLOW AT HIGH PRESSURE. (Hydrogenation of alpha-methylstyrene becomes a liquid limited reaction. Complete wetting is beneficial to this situation. ) n THE PREFERRED MODE FOR SCALE-UP (UPFLOW OR DOWNFLOW) DEPENDS ON THE TYPE OF REACTION SYSTEM AS WELL AS ON THE RANGE OF OPERATING CONDITIONS THAT AFFECT CATALYST WETTING. n FINES NEUTRALIZE PERFORMANCE DIFFERENCES DUE TO MODE OF OPERATION AND REACTION SYSTEM TYPE , DECOUPLE HYDRODYNAMICS AND KINETICS, AND HENCE ARE TO BE PREFERRED AS SCALE-UP TOOLS. n THE TESTED MODELS PREDICT PERFORMANCE WELL (although improvements in mass transfer correlations are necessary) CREL
Drawbacks of Evaluated Models n n n Isothermal Operation Liquid Volatility Effects not Considered Coupling of Hydrodynamics and Transport Ignored Fully Internally Wetted Pellets Assumed Single Component, Dilute Solution Transport Assumed Multicomponent Effects not Considered Simplified Models Accounting for Some of the Above Effects n n Pellet Scale (Level I) Model (Kim and Kim, 1981; Harold, 1988) Reactor Scale (Level II) Model (La. Vopa and Satterfield, 1988; Kheshgi et al. , 1992) Extended Steady State Rigorous (Level III) Model Test Reaction System: Hydrogenation of Cyclohexene CREL
L-III Model Reactor Scale Equations (1 -D) Continuity Species Momentum Energy Fluxes Modeled by Multicomponent Stefan-Maxwell Formulation CREL
L-III Model Catalyst Scale Equations (Extension of Harold, 1988) Liquid Filled Zone Fully Externally Wetted, Partially Liquid Filled Pellet Gas Filled Zone Intra-catalyst G-L Interface Continuity of temperature, mass and energy fluxes, and equilibrium relations between compositions CREL
Simulation Results: Multiplicity Effects • Hysteresis Predicted • Wet Branch Temperature Rise (~10 - • Two Distinct Rate Branches Predicted (As Observed by Hanika, 1975) • Branch Continuation, Ignition and Extinction Points • Wet Branch Conversion (~30 %) • Dry Branch Conversion (> 95 %) 15 o. C) • Dry Branch Temperature Rise -160 o. C) (~140 CREL
Wet Branch Simulation Reactor Scale Hydrodynamics Reactor Scale Species Concentrations Pellet Scale Multicomponent Flux Profiles CREL
Dry Branch Simulation Reactor Scale Hydrodynamics Pellet Scale Pressure Profiles Reactor Scale Species Concentrations Pellet Scale Temperature Profiles CREL
Intra-reactor Wet-Dry Transition • Abrupt drop in liquid flow • Abrupt change in catalyst wetting • Temperature rise after liquidgas transition • Cyclohexene and cyclohexane mole fraction shows evaporation and reaction CREL
Summary n n The reactor scale variation of phase holdups and velocities, multiplicity, and temperature rise were successfully simulated by the developed (LIII) model more rigorously than other models developed earlier Both wet and dry branch temperature, conversion, and corresponding fluxes were successfully modeled by the set of equations developed Intra-pellet reaction-transport equations for the wet and dry zones in presence of multicomponent interactions, evaporation, and condensation were successfully modeled The wet to dry transition prediction requires robust numerical techniques to yield stable solution at pellet scale (for the LIII model), but depicts the observed abrupt transition with a reactor scale (LII) model CREL
- Slides: 25
